Top Analysis Reporting Jobs in Dayton, OH

Design and own a unified data model for an AI-driven pipeline risk platform. Responsibilities include lakehouse and medallion architecture, geospatial modeling, entity resolution, ingestion patterns, governance, lineage, data quality, access controls, and traceability. Partner with data engineers, application engineers, and data scientists to implement schemas, pipelines, serving layers, and optimization strategies while maintaining clear architecture documentation.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.

Leads the data engineering organization and enterprise Databricks Lakehouse on AWS. Owns team development, platform strategy, delivery, reliability, governance, budget, vendors, architecture standards, and regulatory compliance. Partners with executives on data transformation, MDM, ERP migration, analytics, and AI enablement. Requires extensive data engineering leadership, Databricks and AWS expertise, regulated-environment experience, and proven budget and vendor management.

Manage Oracle and PostgreSQL databases across on-premises and AWS environments, including upgrades, migrations, performance tuning, security, and backup recovery. Design and maintain ETL pipelines using Talend, SQL, Power Automate, and related tools. Perform data profiling, quality analysis, governance, and cloud migration activities. Create technical architecture and lineage documentation while supporting regulated, audit-ready data platforms and integrations.

Lead the architecture, design, development, troubleshooting, and optimization of Snowflake data solutions for higher education clients. Conduct discovery and design workshops, assess existing environments, create enterprise data models and future-state architectures, develop ETL/ELT pipelines, implement security and data-quality controls, and optimize performance and costs. Serve as a client-facing technical advisor, translate business requirements into scalable solutions, lead technical workstreams, support business development, mentor teams, and travel periodically.

Leads analytics engineering and analytics-ready data architecture for government clients. Designs standardized data models, transformation logic, validation frameworks, and reusable integration patterns. Governs data quality, QA, backfills, and release processes while resolving complex data issues. Integrates web, email, social, survey, and client-system data to support dashboards, reporting, measurement, and insights. Advises stakeholders, influences enterprise standards, coordinates with product teams, and supports client-facing analytics workstreams.

Own measurement strategies for large omnichannel brands, including test design, marketing mix modeling, incrementality analysis, attribution interpretation, and budget recommendations. Translate complex findings into actionable guidance for executives and marketing teams, support prospect conversations, identify customer and product gaps, and collaborate with Product, Data Science, and Customer Success. The role requires strong paid media expertise, omnichannel fluency, statistical measurement literacy, and the ability to communicate uncertainty and recommendations clearly.

Build and operate reliable ETL and ELT pipelines across lakehouse and transactional systems. Develop data models, enforce governance, integrate diverse data sources, and support analytics, APIs, and predictive tools. Monitor performance, data quality, lineage, cost, and uptime while collaborating with data science, AI, product, and innovation teams.

Design and operate Alpaca’s scalable data platform on GCP, including lakehouse infrastructure, Kubernetes-based deployments, streaming and CDC pipelines, batch ingestion, BI access, cataloging, monitoring, and governance. Build infrastructure as code with Terraform and Ansible, operate distributed query engines and Apache Iceberg, maintain reliability practices, and collaborate with DevOps and analytics teams to support rapidly evolving data requirements.

We are seeking an experienced data analyst to maximize our service offerings through data mining, generation, and visualization, while producing goal-oriented reports.